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Proceedings Paper

Integrating models to predict the reason of unknown-caused grassland fire based on GIS
Author(s): Zhengxiang Zhang; Guanglei Hou; Hongyan Zhang; Daowei Zhou
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Paper Abstract

This study predicts the reason of unknown-caused fires that occurred in grassland in the east of Inner Mongolia, China. GIS and logistic regression are used to build the predicting models. The causes of grassland fires were classified as vehicle, production, living and lighting. The areas were divided into fired and unfired grid cells (500m*500m) with spatial analysis, in order to determine the spatial factors and weather factors, such as the nearest distance to villages, roads, fields etc. Logistic regression was used to build predictive models of the probability for each reason of grassland fires. Four probabilities of each unknown-caused grassland fire were calculated and the maximum value expresses the fire reason. The results show that natural fires are less than human-caused grassland fires and they can be used in fire risk models and to support fire management decision-making. These methods would take advantage to the other grassland fire studies, such as fire ecology, fire weather, fire cycle, etc.

Paper Details

Date Published: 15 October 2009
PDF: 9 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 749242 (15 October 2009); doi: 10.1117/12.838567
Show Author Affiliations
Zhengxiang Zhang, Northeast Normal Univ. (China)
Guanglei Hou, Northeast Normal Univ. (China)
Hongyan Zhang, Northeast Normal Univ. (China)
Daowei Zhou, Northeast Normal Univ. (China)
Northeast Institute of Geography and Agroecology (China)

Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

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